Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
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Updated
Jan 14, 2023 - Python
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Official implementation of Score-CAM in PyTorch
Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]
tensorflow implementation of Grad-CAM (CNN visualization)
A Simple pytorch implementation of GradCAM and GradCAM++
Neural network visualization toolkit for tf.keras
Visualizing Yolov5's layers using GradCam
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
This repository contains all the work that I regularly did and studied from Medium blogs, several research papers, and other Repos (related/unrelated to the research papers).
Pytorch implementation of various neural network interpretability methods
DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN models with GradCam score for interpretability,
vizgradcam is the fastest way to visualize GradCAM with your Keras models.
Gcam is an easy to use Pytorch library that makes model predictions more interpretable for humans. It allows the generation of attention maps with multiple methods like Guided Backpropagation, Grad-Cam, Guided Grad-Cam and Grad-Cam++.
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
A toolkit for efficent computation of saliency maps for explainable AI attribution. This tool was developed at Lawrence Livermore National Laboratory.
PyTorch implementation of pulse measurement neural networks.
tensorflow.keras implementation of gradcam and gradcam++
Visualizing VGG16 Convolutional Neural Network using Keras
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